# Monitoring View

The Monitoring View allows you to see the live feed of the vision sensor.

Click Enter Monitoring View on the Home Page or in the Finalize step to enter Monitoring View.

## Monitoring View Page Layout

The screenshot below shows the Monitoring View of the Anomaly Detector app. This screen consists of the live feed in the center and information about the images on the right sidebar. You can see as the vision sensor takes images in action and adds them to the list in the sidebar.

The layout and most of the features of the Monitoring View are the same for all apps. However, there are some slight differences. For example, a Classifier app shows the class of the images on the Monitoring View, but the Anomaly Detector does not.

1 | This is the live feed of the vision sensor with overlay graphics, such as the rectangle of the ROI or the trigger of the fixture.
2 | Click Exit Monitoring View to exit.
3 | This is the sidebar with the list of images and additional information.
4 | The sidebar shows a time stamp for each image.
5 | The sidebar shows the confidence level of the vision sensor for each image.
6 | This section shows the following statistics: Cycle Time: The time between the trigger event and the processed result. OK/NG/ERR: The number of OK, NG, and ERR images. Note: The 4-Class Classifier app calls these Pass, Fail, and ERR. Fail is for the classes that are set to fail. For more information, see Train 4-Class Classifier. SFTP Errors: The number of SFTP errors.
7 | Click Reset Counts to clear the counters. All statistics are reset to zero, except for the Cycle Time.
8 | This indicator shows whether the Outputs setting is enabled.
9 | This indicator shows whether the Inputs setting is enabled.
10 | Click to open the Inputs settings.
11 | This indicator shows the Trigger Mode setting of the vision sensor.
12 | This section lets you choose how you want to see the live feed of the vision sensor. You have the following options: Click View to focus on the Region of Interest. For the Anomaly Detector, click Heat Map to highlight the areas that the vision sensor sees as an anomaly. For the Classifiers, click Text to show the label of the class on the live feed.

## Sidebars of the Different Apps in Monitoring View

Check the screenshots of the different sidebars below and note the differences:

- The confidence indicator corresponds to the style of the application.

- When using one of the Classifiers, the Monitoring View also shows the class of the images.

- The Anomaly Detector and the 2-Class Classifier apps count OK/NG/ERR images. The 4-Class Classifier uses the Pass, the Fail, and the ERR statistics.

- The Classifier can label images as Unclassified if the app is not properly trained. For example, if the fixture is missing or the ROI is out of bounds. Unclassified images count as an error (ERR).

Anomaly Detector | 2-Class Classifier | 4-Class Classifier